Abstract: A computer-implemented method including receiving, at a computing device, a first treatment plan designed to treat a sexual performance health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the sexual performance health issue, enable the user to perform an exercise at different exertion levels. While the user uses a treatment apparatus to perform the first treatment plan for the user, the computing device receives cardiovascular data from one or more sensors configured to measure the cardiovascular data associated with the user, and transmits the cardiovascular data. A machine learning model is used to generate a second treatment plan that modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the cardiovascular data, and the cardiovascular health issue of the user. The method includes receiving the second treatment plan.

Abstract: A computer-implemented system includes an interface comprising a display configured to display interface presentation data pertaining to a user using an electromechanical machine to perform a treatment plan and one or more processing devices configured to receive selected measurement information associated with the user and treatment plan information associated with the treatment plan, generate the interface presentation data based on the selected measurement information and the treatment plan information, and enable the interface to present, in a portion of the display, the interface presentation data for the user. The portion of the display includes one or more graphical elements that present, in real-time or near real-time, at least one type of the selected measurement information and the treatment plan information.

Abstract: A computer-implemented method is disclosed. The method includes determining whether one or more messages have been received while a user performs a treatment plan. The one or more messages may pertain to at least one of a user and a usage of the electromechanical machine by the user. The electromechanical machine may be configured to be manipulated by the user while the user is performing a treatment plan. The method also includes, responsive to determining that the one or more messages have not been received, determining, using one or more machine learning models, one or more preventative actions to perform. The method also includes causing the one or more preventative actions to be performed.

Abstract: A computer-implemented method is disclosed. The method includes receiving, at a computing device, a first treatment plan designed to treat an invasive surgical-related health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the invasive surgical-related health issue, enable the user to perform an exercise at different exertion levels. Next, while the user uses the electromechanical machine to perform the first treatment plan, receiving, at the computing device, data from sensors configured to measure the data associated with the invasive surgical-related health issue and transmitting the data. One or more machine learning models are used to generate a second treatment plan. The second treatment plan modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the data, and the invasive surgical-related health issue. The method additionally includes receiving the second treatment plan.

Abstract: A computer-implemented system may include a rowing machine, an interface comprising a display configured to present information pertaining to the treatment plan, and at least one processing device configured to receive, from sensors, measurements associated with the user, wherein the measurements are received while the user performs the treatment plan; determine, via machine learning models, content items to present to the user, wherein the determining is based on the measurements and one or more characteristics of the user; and while the user performs the treatment plan using the rowing machine, cause presentation of the content items on the interface, wherein the content items comprise at least information related to a state of the user, and the state of the user is associated with the measurements, the characteristics, or some combination thereof.

Abstract: A smart exercise device includes an interface comprising a smart mirror configured to present information pertaining to a treatment plan being performed by a user while the user interacts with the smart exercise device. A processing device is configured to cause the smart exercise device to perform one or more functions related to the treatment plan, such as cause one or more preventative actions to be performed based on whether the processing device receives one or more messages, cause one or more content items to be presented to the user on the interface, assign the treatment plan to the smart exercise device based on a determined eligibility of the user, and implement the treatment plan to reduce a probability of a cardiac intervention for the user.

Abstract: Systems, methods, and computer-readable media for assigning remote monitoring sessions. The system includes an electromechanical machine, one or more sensors, and one or more processing devices. The electromechanical machine is configured to be manipulated by a user while performing a treatment plan. The one or more sensors are configured to determine measurements of one or more vital signs associated with the user. The one or more processing devices are configured to receive a request to conduct a monitored session of the user performing the treatment plan. The one or more processing devices are also configured to determine whether conducting the monitored session with a computing device will violate one or more remote monitoring rules. The one or more processing device are further configured to initiate the monitored session by displaying the measurements on a display of the computing device while the user performs the treatment plan.

Abstract: A computer-implemented system includes one or more processing devices configured to receive user information associated with a user, generate a selected set of the user information, determine, based on the selected set of the user information, at least one of a first probability of surviving one or more procedures and a second probability indicating an improvement, resulting from the one or more procedures, in quality-of-life metrics for the user, generate, based on the at least one of the first probability and the second probability and on the selected set of the user information, one or more recommendations of whether the user should undergo the one or more procedures, and generate, based on the one or more recommendations, a treatment plan that includes one or more exercises directed to modifying the at least one of the first probability and the second probability.

Abstract: A computer-implemented method including receiving, at a computing device, a first treatment plan designed to treat a cardiovascular health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the cardiovascular health issue, enable the user to perform an exercise at different exertion levels. While the user uses a treatment apparatus to perform the first treatment plan for the user, the computing device receives cardiovascular data from one or more sensors configured to measure the cardiovascular data associated with the user, and transmits the cardiovascular data. Wherein a machine learning model is used to generate a second treatment plan. The second treatment plan modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the cardiovascular data, and the cardiovascular health issue of the user. The method includes receiving the second treatment plan.

Abstract: A computer-implemented method including receiving, at a computing device, a first treatment plan designed to treat a sexual performance health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the sexual performance health issue, enable the user to perform an exercise at different exertion levels. While the user uses a treatment apparatus to perform the first treatment plan for the user, the computing device receives cardiovascular data from one or more sensors configured to measure the cardiovascular data associated with the user, and transmits the cardiovascular data. A machine learning model is used to generate a second treatment plan that modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the cardiovascular data, and the cardiovascular health issue of the user. The method includes receiving the second treatment plan.

Abstract: A computer-implemented system includes an interface comprising a display configured to display interface presentation data pertaining to a user using an electromechanical machine to perform a treatment plan and one or more processing devices configured to receive selected measurement information associated with the user and treatment plan information associated with the treatment plan, generate the interface presentation data based on the selected measurement information and the treatment plan information, and enable the interface to present, in a portion of the display, the interface presentation data for the user. The portion of the display includes one or more graphical elements that present, in real-time or near real-time, at least one type of the selected measurement information and the treatment plan information.

Abstract: A computer-implemented system includes one or more processing devices configured to receive comorbidity information that includes a plurality of comorbidities or comorbidity-related conditions associated with a user, generate a selected set of the comorbidity information, determine, based on the selected set of the comorbidity information, respective probabilities of a plurality of different outcomes related to the comorbidity information, and generate, based on the respective probabilities and the selected set of the comorbidity information, a treatment plan comprising one or more exercises directed to changing the respective probabilities. A treatment apparatus is configured to implement the treatment plan while the treatment apparatus is being manipulated by the user.

Abstract: A computer-implemented method is disclosed. The method includes receiving, at a computing device, a first treatment plan designed to treat an invasive surgical-related health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the invasive surgical-related health issue, enable the user to perform an exercise at different exertion levels. Next, while the user uses the electromechanical machine to perform the first treatment plan, receiving, at the computing device, data from sensors configured to measure the data associated with the invasive surgical-related health issue and transmitting the data. One or more machine learning models are used to generate a second treatment plan. The second treatment plan modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the data, and the invasive surgical-related health issue. The method additionally includes receiving the second treatment plan.

Abstract: In one embodiment, a computer-implemented system includes an electromechanical machine configured to be manipulated by a user while the user performs a treatment plan. The treatment plan includes a high-intensity interval training (HIIT) session. A processing device is configured to initiate, using the electromechanical machine, the HIIT session, receive, via one or more sensors, one or more measurements pertaining to the electromechanical machine, determine whether the one or more measurements exceed one or more of one or more corresponding thresholds, and in response to determining that the one or more measurements exceed one or more of the one or more corresponding thresholds, modify the treatment plan to cause operation of the electromechanical machine to be modified.

Abstract: A computer-implemented method is disclosed. The method includes receiving, from one or more sensors, one or more measurements associated with a user, where the one or more measurements are received while the user performs a treatment plan, and an electromechanical machine is configured to be manipulated by the user while the user is performing the treatment plan. The method also includes determining, via one or more machine learning models, one or more content items to present to the user, where the determining is based on the one or more measurements and one or more characteristics of the user. A presentation of the one or more content items is provided on an interface while the user performs the treatment plan using the electromechanical machine.

Abstract: A treadmill includes one or more processing devices configured to receive a plurality of risk factors associated with at least one of a cardiac condition and a cardiac outcome for a user, generate a selected set of the risk factors, determine, based on the selected set of the risk factors, a probability of a cardiac intervention, generate, based on the probability and the selected set of the risk factors, a treatment plan to be performed by the user while the user interacts with the treadmill, the treatment plan including one or more exercises directed to reducing the probability of the cardiac intervention, and controlling, based on the treatment plan, the treadmill to at least one of actuate a motor to adjust a speed of the treadmill and adjust an incline of a belt.

Abstract: A computer-implemented method is disclosed. The method includes receiving, at a computing device, a first treatment plan designed to treat an invasive surgical-related health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the invasive surgical-related health issue, enable the user to perform an exercise at different exertion levels. Next, while the user uses the electromechanical machine to perform the first treatment plan, receiving, at the computing device, data from sensors configured to measure the data associated with the invasive surgical-related health issue and transmitting the data. One or more machine learning models are used to generate a second treatment plan. The second treatment plan modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the data, and the invasive surgical-related health issue. The method additionally includes receiving the second treatment plan.

Abstract: A computer-implemented system includes one or more processing devices configured to receive a plurality of risk factors associated with at least one of a cardiac condition and a cardiac outcome for a user, generate a selected set of the risk factors, determine, based on the selected set of the risk factors, a probability that a cardiac-related intervention will occur, and generate, based on the probability and the selected set of the risk factors, a treatment plan including one or more exercises directed to reducing the probability that the cardiac-related intervention will occur, and a stair-climbing machine configured to implement the treatment plan while the stair-climbing machine is being manipulated by the user.

Abstract: A smart exercise device includes a smart mirror configured to present information pertaining to a treatment plan being performed by a user and one or more processing devices configured to receive a plurality of risk factors associated with at least one of a cardiac condition and a cardiac outcome, generate a selected set of the risk factors, determine, based on the selected set of the risk factors, a probability that a cardiac intervention will occur, generate, based on the probability and the selected set of the risk factors, the treatment plan, and, to facilitate conformity with the treatment plan, cause the smart mirror to display a visual cue in response to a deviation of the user from at least one of a desired body posture, a range of motion, a joint or limb angle, and a motion defined by the treatment plan.

Abstract: A computer-implemented system includes a processing device configured to receive a plurality of user and blood vessel characteristics associated with a user, generate a selected set of user and blood vessel characteristics, determine, based on the selected set of the user and blood vessel characteristics, a probability that angiogenesis will occur, and generate, based on the probability and the selected set of the user and blood vessel characteristics, a treatment plan that includes one or more exercises directed to modifying the probability that angiogenesis will occur, and a treatment apparatus configured to implement the treatment plan while the treatment apparatus is being manipulated by the user.